Added python aliases for face predict overloaded functions

modules/face/include/opencv2/face.hpp

@@ -256,7 +256,7 @@ public:
     CV_WRAP virtual void update(InputArrayOfArrays src, InputArray labels);
 
     /** @overload */
-    CV_WRAP int predict(InputArray src) const;
+    CV_WRAP_AS(predict_label) int predict(InputArray src) const;
 
 
     /** @brief Predicts a label and associated confidence (e.g. distance) for a given input image.
@@ -300,12 +300,11 @@ public:
     /** @brief - if implemented - send all result of prediction to collector that can be used for somehow custom result handling
     @param src Sample image to get a prediction from.
     @param collector User-defined collector object that accepts all results
-    @param state - optional user-defined state token that should be passed back from FaceRecognizer implementation
 
     To implement this method u just have to do same internal cycle as in predict(InputArray src, CV_OUT int &label, CV_OUT double &confidence) but
     not try to get "best@ result, just resend it to caller side with given collector
     */
-    CV_WRAP virtual void predict(InputArray src, Ptr<PredictCollector> collector, const int state = 0) const = 0;
+    CV_WRAP_AS(predict_collect) virtual void predict(InputArray src, Ptr<PredictCollector> collector) const = 0;
 
     /** @brief Saves a FaceRecognizer and its model state.
 

modules/face/src/eigen_faces.cpp

@@ -42,7 +42,7 @@ public:
     void train(InputArrayOfArrays src, InputArray labels);
 
     // Send all predict results to caller side for custom result handling
-    void predict(InputArray src, Ptr<PredictCollector> collector, const int state) const;
+    void predict(InputArray src, Ptr<PredictCollector> collector) const;
 };
 
 //------------------------------------------------------------------------------
@@ -99,7 +99,7 @@ void Eigenfaces::train(InputArrayOfArrays _src, InputArray _local_labels) {
     }
 }
 
-void Eigenfaces::predict(InputArray _src, Ptr<PredictCollector> collector, const int state) const {
+void Eigenfaces::predict(InputArray _src, Ptr<PredictCollector> collector) const {
     // get data
     Mat src = _src.getMat();
     // make sure the user is passing correct data
@@ -114,11 +114,11 @@ void Eigenfaces::predict(InputArray _src, Ptr<PredictCollector> collector, const
     }
     // project into PCA subspace
     Mat q = LDA::subspaceProject(_eigenvectors, _mean, src.reshape(1, 1));
-    collector->init((int)_projections.size(), state);
+    collector->init(_projections.size());
     for (size_t sampleIdx = 0; sampleIdx < _projections.size(); sampleIdx++) {
         double dist = norm(_projections[sampleIdx], q, NORM_L2);
         int label = _labels.at<int>((int)sampleIdx);
-        if (!collector->collect(label, dist, state))return;
+        if (!collector->collect(label, dist))return;
     }
 }
 

modules/face/src/facerec.cpp

@@ -80,10 +80,10 @@ int FaceRecognizer::predict(InputArray src) const {
 }
 
 void FaceRecognizer::predict(InputArray src, CV_OUT int &label, CV_OUT double &confidence) const {
-    Ptr<MinDistancePredictCollector> collector = MinDistancePredictCollector::create(getThreshold());
-    predict(src, collector, 0);
-    label = collector->getLabel();
-    confidence = collector->getDist();
+    Ptr<StandardCollector> collector = StandardCollector::create(getThreshold());
+    predict(src, collector);
+    label = collector->getMinLabel();
+    confidence = collector->getMinDist();
 }
 
 }

modules/face/src/fisher_faces.cpp

@@ -37,7 +37,7 @@ public:
     void train(InputArrayOfArrays src, InputArray labels);
 
     // Send all predict results to caller side for custom result handling
-    void predict(InputArray src, Ptr<PredictCollector> collector, const int state) const;
+    void predict(InputArray src, Ptr<PredictCollector> collector) const;
 };
 
 // Removes duplicate elements in a given vector.
@@ -120,7 +120,7 @@ void Fisherfaces::train(InputArrayOfArrays src, InputArray _lbls) {
     }
 }
 
-void Fisherfaces::predict(InputArray _src, Ptr<PredictCollector> collector, const int state) const {
+void Fisherfaces::predict(InputArray _src, Ptr<PredictCollector> collector) const {
     Mat src = _src.getMat();
     // check data alignment just for clearer exception messages
     if(_projections.empty()) {
@@ -134,11 +134,11 @@ void Fisherfaces::predict(InputArray _src, Ptr<PredictCollector> collector, cons
     // project into LDA subspace
     Mat q = LDA::subspaceProject(_eigenvectors, _mean, src.reshape(1,1));
     // find 1-nearest neighbor
-    collector->init((int)_projections.size(), state);
+    collector->init((int)_projections.size());
     for (size_t sampleIdx = 0; sampleIdx < _projections.size(); sampleIdx++) {
         double dist = norm(_projections[sampleIdx], q, NORM_L2);
         int label = _labels.at<int>((int)sampleIdx);
-        if (!collector->collect(label, dist, state))return;
+        if (!collector->collect(label, dist))return;
     }
 }
 

modules/face/src/lbph_faces.cpp

@@ -92,7 +92,7 @@ public:
     void update(InputArrayOfArrays src, InputArray labels);
 
     // Send all predict results to caller side for custom result handling
-    void predict(InputArray src, Ptr<PredictCollector> collector, const int state = 0) const;
+    void predict(InputArray src, Ptr<PredictCollector> collector) const;
 
     // See FaceRecognizer::load.
     void load(const FileStorage& fs);
@@ -383,7 +383,7 @@ void LBPH::train(InputArrayOfArrays _in_src, InputArray _in_labels, bool preserv
     }
 }
 
-void LBPH::predict(InputArray _src, Ptr<PredictCollector> collector, const int state) const {
+void LBPH::predict(InputArray _src, Ptr<PredictCollector> collector) const {
     if(_histograms.empty()) {
         // throw error if no data (or simply return -1?)
         String error_message = "This LBPH model is not computed yet. Did you call the train method?";
@@ -399,11 +399,11 @@ void LBPH::predict(InputArray _src, Ptr<PredictCollector> collector, const int s
             _grid_y, /* grid size y */
             true /* normed histograms */);
     // find 1-nearest neighbor
-    collector->init((int)_histograms.size(), state);
+    collector->init((int)_histograms.size());
     for (size_t sampleIdx = 0; sampleIdx < _histograms.size(); sampleIdx++) {
         double dist = compareHist(_histograms[sampleIdx], query, HISTCMP_CHISQR_ALT);
         int label = _labels.at<int>((int)sampleIdx);
-        if (!collector->collect(label, dist, state))return;
+        if (!collector->collect(label, dist))return;
     }
 }
 

modules/face/src/map_predict_collector.cpp

-/*
-By downloading, copying, installing or using the software you agree to this license.
-If you do not agree to this license, do not download, install,
-copy or use the software.
-
-
-License Agreement
-For Open Source Computer Vision Library
-(3-clause BSD License)
-
-Copyright (C) 2000-2015, Intel Corporation, all rights reserved.
-Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
-Copyright (C) 2009-2015, NVIDIA Corporation, all rights reserved.
-Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
-Copyright (C) 2015, OpenCV Foundation, all rights reserved.
-Copyright (C) 2015, Itseez Inc., all rights reserved.
-Third party copyrights are property of their respective owners.
-
-Redistribution and use in source and binary forms, with or without modification,
-are permitted provided that the following conditions are met:
-
-* Redistributions of source code must retain the above copyright notice,
-this list of conditions and the following disclaimer.
-
-* Redistributions in binary form must reproduce the above copyright notice,
-this list of conditions and the following disclaimer in the documentation
-and/or other materials provided with the distribution.
-
-* Neither the names of the copyright holders nor the names of the contributors
-may be used to endorse or promote products derived from this software
-without specific prior written permission.
-
-This software is provided by the copyright holders and contributors "as is" and
-any express or implied warranties, including, but not limited to, the implied
-warranties of merchantability and fitness for a particular purpose are disclaimed.
-In no event shall copyright holders or contributors be liable for any direct,
-indirect, incidental, special, exemplary, or consequential damages
-(including, but not limited to, procurement of substitute goods or services;
-loss of use, data, or profits; or business interruption) however caused
-and on any theory of liability, whether in contract, strict liability,
-or tort (including negligence or otherwise) arising in any way out of
-the use of this software, even if advised of the possibility of such damage.
-*/
-#include "opencv2/face/predict_collector.hpp"
-#include "opencv2/core/cvstd.hpp"
-#include <iterator>
-namespace cv {
-namespace face {
-
-CV_WRAP bool MapPredictCollector::emit(const int label, const double dist, const int state)
-{
-    ((void)state);
-    //if already in index check which is closer
-    if (_idx->find(label) != _idx->end()) {
-        double current = (*_idx)[label];
-        if (dist < current) {
-            (*_idx)[label] = dist;
-        }
-    }
-    else {
-        (*_idx)[label] = dist;
-    }
-    return true;
-}
-
-Ptr<std::map<int, double> > MapPredictCollector::getResult()
-{
-    return _idx;
-}
-
-CV_WRAP std::vector<std::pair<int, double> > MapPredictCollector::getResultVector()
-{
-    std::vector<std::pair<int, double> > result;
-    std::copy(_idx->begin(), _idx->end(), std::back_inserter(result));
-    return result;
-}
-
-CV_WRAP Ptr<MapPredictCollector> MapPredictCollector::create(double threshold)
-{
-    return Ptr<MapPredictCollector>(new MapPredictCollector(threshold));
-}
-
-
-
-}
-}
\ No newline at end of file

modules/face/src/mindist_predict_collector.cpp

-/*
-By downloading, copying, installing or using the software you agree to this license.
-If you do not agree to this license, do not download, install,
-copy or use the software.
-
-
-License Agreement
-For Open Source Computer Vision Library
-(3-clause BSD License)
-
-Copyright (C) 2000-2015, Intel Corporation, all rights reserved.
-Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
-Copyright (C) 2009-2015, NVIDIA Corporation, all rights reserved.
-Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
-Copyright (C) 2015, OpenCV Foundation, all rights reserved.
-Copyright (C) 2015, Itseez Inc., all rights reserved.
-Third party copyrights are property of their respective owners.
-
-Redistribution and use in source and binary forms, with or without modification,
-are permitted provided that the following conditions are met:
-
-* Redistributions of source code must retain the above copyright notice,
-this list of conditions and the following disclaimer.
-
-* Redistributions in binary form must reproduce the above copyright notice,
-this list of conditions and the following disclaimer in the documentation
-and/or other materials provided with the distribution.
-
-* Neither the names of the copyright holders nor the names of the contributors
-may be used to endorse or promote products derived from this software
-without specific prior written permission.
-
-This software is provided by the copyright holders and contributors "as is" and
-any express or implied warranties, including, but not limited to, the implied
-warranties of merchantability and fitness for a particular purpose are disclaimed.
-In no event shall copyright holders or contributors be liable for any direct,
-indirect, incidental, special, exemplary, or consequential damages
-(including, but not limited to, procurement of substitute goods or services;
-loss of use, data, or profits; or business interruption) however caused
-and on any theory of liability, whether in contract, strict liability,
-or tort (including negligence or otherwise) arising in any way out of
-the use of this software, even if advised of the possibility of such damage.
-*/
-#include "opencv2/face/predict_collector.hpp"
-#include "opencv2/core/cvstd.hpp"
-namespace cv {
-namespace face {
-
-bool MinDistancePredictCollector::emit(const int label, const double dist, const int state) {
-    ((void)state);
-    _label = label;
-    _dist = dist;
-    return true;
-}
-
-CV_WRAP bool MinDistancePredictCollector::filter(int* label, double* dist, const int state)
-{
-    ((void)label);
-    ((void)state);
-    return *dist < _dist;
-}
-
-int MinDistancePredictCollector::getLabel() const {
-    return _label;
-}
-
-double MinDistancePredictCollector::getDist() const {
-    return _dist;
-}
-
-Ptr<MinDistancePredictCollector> MinDistancePredictCollector::create(double threshold) {
-    return Ptr<MinDistancePredictCollector>(new MinDistancePredictCollector(threshold));
-}
-
-}
-}
\ No newline at end of file

modules/face/src/predict_collector.cpp

@@ -42,117 +42,73 @@ or tort (including negligence or otherwise) arising in any way out of
 the use of this software, even if advised of the possibility of such damage.
 */
 #include "opencv2/face/predict_collector.hpp"
-#include "opencv2/core/cvstd.hpp"
-namespace cv {
-namespace face {
 
+namespace cv {namespace face {
 
-void PredictCollector::init(const int size, const int state) {
-    //reserve for some-how usage in descendants
-    _size = size;
-    _state = state;
+static std::pair<int, double> toPair(const StandardCollector::PredictResult & val) {
+    return std::make_pair(val.label, val.distance);
 }
 
-CV_WRAP bool PredictCollector::defaultFilter(int * label, double * dist, const int state)
-{
-    // if state provided we should compare it with current state
-    if (_state != 0 && _state != state) {
-        return false;
-    }
-
-    // if exclude label provided we can test it first
-    if (_excludeLabel != 0 && _excludeLabel == *label) {
-        return false;
-    }
-
-    // initially we must recalculate distance by koef iv given
-    if (_distanceKoef != 1) {
-        *dist = *dist * _distanceKoef;
-    }
-    // check upper threshold
-    if (*dist > _threshold) {
-        return false;
-    }
-    //check inner threshold
-    if (*dist < _minthreshold) {
-        return false;
-    }
-
-    return true;
+static bool pairLess(const std::pair<int, double> & lhs, const std::pair<int, double> & rhs) {
+    return lhs.second < rhs.second;
 }
 
-CV_WRAP bool PredictCollector::filter(int* label, double* dist, const int state)
-{
-    ((void)label);
-    ((void)dist);
-    ((void)state);
-    return true; //no custom logic at base level
+//===================================
+
+StandardCollector::StandardCollector(double threshold_) : threshold(threshold_) {
+    init(0);
 }
 
-bool PredictCollector::emit(const int label, const double dist, const int state) {
-    ((void)label);
-    ((void)dist);
-    ((void)state);
-    return false; // terminate prediction - no any behavior in base PredictCollector
+void StandardCollector::init(size_t size) {
+    minRes = PredictResult();
+    data.clear();
+    data.reserve(size);
 }
 
-CV_WRAP bool PredictCollector::collect(int label, double dist, const int state)
-{
-    if (defaultFilter(&label, &dist, state) && filter(&label,&dist,state)) {
-        return emit(label, dist, state);
+bool StandardCollector::collect(int label, double dist) {
+    if (dist < threshold)
+    {
+        PredictResult res(label, dist);
+        if (res.distance < minRes.distance)
+            minRes = res;
+        data.push_back(res);
     }
     return true;
 }
 
-CV_WRAP int PredictCollector::getSize()
-{
-    return _size;
+int StandardCollector::getMinLabel() const {
+    return minRes.label;
 }
 
-CV_WRAP void PredictCollector::setSize(int size)
-{
-    _size = size;
+double StandardCollector::getMinDist() const {
+    return minRes.distance;
 }
 
-CV_WRAP int PredictCollector::getState()
-{
-    return _state;
-}
-
-CV_WRAP void PredictCollector::setState(int state)
-{
-    _state = state;
-}
-
-CV_WRAP int PredictCollector::getExcludeLabel()
-{
-    return _excludeLabel;
-}
-
-CV_WRAP void PredictCollector::setExcludeLabel(int excludeLabel)
-{
-    _excludeLabel = excludeLabel;
-}
-
-CV_WRAP double PredictCollector::getDistanceKoef()
-{
-    return _distanceKoef;
-}
-
-CV_WRAP void PredictCollector::setDistanceKoef(double distanceKoef)
-{
-    _distanceKoef = distanceKoef;
-}
-
-CV_WRAP double PredictCollector::getMinThreshold()
-{
-    return _minthreshold;
+std::vector< std::pair<int, double> > StandardCollector::getResults(bool sorted) const {
+    std::vector< std::pair<int, double> > res(data.size());
+    std::transform(data.begin(), data.end(), res.begin(), &toPair);
+    if (sorted)
+    {
+        std::sort(res.begin(), res.end(), &pairLess);
+    }
+    return res;
+}
+
+std::map<int, double> StandardCollector::getResultsMap() const {
+    std::map<int, double> res;
+    for (std::vector<PredictResult>::const_iterator i = data.begin(); i != data.end(); ++i) {
+        std::map<int, double>::iterator j = res.find(i->label);
+        if (j == res.end()) {
+            res.insert(toPair(*i));
+        } else if (i->distance < j->second) {
+            j->second = i->distance;
+        }
+    }
+    return res;
 }
 
-CV_WRAP void PredictCollector::setMinThreshold(double minthreshold)
-{
-    _minthreshold = minthreshold;
+Ptr<StandardCollector> StandardCollector::create(double threshold) {
+    return makePtr<StandardCollector>(threshold);
 }
 
-}
-}
\ No newline at end of file
+}} // cv::face::

modules/face/src/stat_predict_collector.cpp

-/*
-By downloading, copying, installing or using the software you agree to this license.
-If you do not agree to this license, do not download, install,
-copy or use the software.
-
-
-License Agreement
-For Open Source Computer Vision Library
-(3-clause BSD License)
-
-Copyright (C) 2000-2015, Intel Corporation, all rights reserved.
-Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
-Copyright (C) 2009-2015, NVIDIA Corporation, all rights reserved.
-Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
-Copyright (C) 2015, OpenCV Foundation, all rights reserved.
-Copyright (C) 2015, Itseez Inc., all rights reserved.
-Third party copyrights are property of their respective owners.
-
-Redistribution and use in source and binary forms, with or without modification,
-are permitted provided that the following conditions are met:
-
-* Redistributions of source code must retain the above copyright notice,
-this list of conditions and the following disclaimer.
-
-* Redistributions in binary form must reproduce the above copyright notice,
-this list of conditions and the following disclaimer in the documentation
-and/or other materials provided with the distribution.
-
-* Neither the names of the copyright holders nor the names of the contributors
-may be used to endorse or promote products derived from this software
-without specific prior written permission.
-
-This software is provided by the copyright holders and contributors "as is" and
-any express or implied warranties, including, but not limited to, the implied
-warranties of merchantability and fitness for a particular purpose are disclaimed.
-In no event shall copyright holders or contributors be liable for any direct,
-indirect, incidental, special, exemplary, or consequential damages
-(including, but not limited to, procurement of substitute goods or services;
-loss of use, data, or profits; or business interruption) however caused
-and on any theory of liability, whether in contract, strict liability,
-or tort (including negligence or otherwise) arising in any way out of
-the use of this software, even if advised of the possibility of such damage.
-*/
-#include "opencv2/face/predict_collector.hpp"
-#include "opencv2/core/cvstd.hpp"
-namespace cv {
-namespace face {
-
-CV_WRAP bool StatPredictCollector::emit(const int label, const double dist, const int state) {
-    ((void)state);
-    ((void)label);
-    _count++;
-    _sum += dist;
-    if (_min > dist) {
-        _min = dist;
-    }
-    if (_max < dist) {
-        _max = dist;
-    }
-    return true;
-}
-CV_WRAP double StatPredictCollector::getMin()
-{
-    return _min;
-}
-
-CV_WRAP double StatPredictCollector::getMax()
-{
-    return _max;
-}
-
-CV_WRAP double StatPredictCollector::getSum()
-{
-    return _sum;
-}
-
-CV_WRAP int StatPredictCollector::getCount()
-{
-    return _count;
-}
-
-CV_WRAP Ptr<StatPredictCollector> StatPredictCollector::create(double threshold) {
-    return Ptr<StatPredictCollector>(new StatPredictCollector(threshold));
-}
-
-}
-}
\ No newline at end of file

modules/face/src/std_predict_collector.cpp

-/*
-By downloading, copying, installing or using the software you agree to this license.
-If you do not agree to this license, do not download, install,
-copy or use the software.
-
-
-License Agreement
-For Open Source Computer Vision Library
-(3-clause BSD License)
-
-Copyright (C) 2000-2015, Intel Corporation, all rights reserved.
-Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
-Copyright (C) 2009-2015, NVIDIA Corporation, all rights reserved.
-Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
-Copyright (C) 2015, OpenCV Foundation, all rights reserved.
-Copyright (C) 2015, Itseez Inc., all rights reserved.
-Third party copyrights are property of their respective owners.
-
-Redistribution and use in source and binary forms, with or without modification,
-are permitted provided that the following conditions are met:
-
-* Redistributions of source code must retain the above copyright notice,
-this list of conditions and the following disclaimer.
-
-* Redistributions in binary form must reproduce the above copyright notice,
-this list of conditions and the following disclaimer in the documentation
-and/or other materials provided with the distribution.
-
-* Neither the names of the copyright holders nor the names of the contributors
-may be used to endorse or promote products derived from this software
-without specific prior written permission.
-
-This software is provided by the copyright holders and contributors "as is" and
-any express or implied warranties, including, but not limited to, the implied
-warranties of merchantability and fitness for a particular purpose are disclaimed.
-In no event shall copyright holders or contributors be liable for any direct,
-indirect, incidental, special, exemplary, or consequential damages
-(including, but not limited to, procurement of substitute goods or services;
-loss of use, data, or profits; or business interruption) however caused
-and on any theory of liability, whether in contract, strict liability,
-or tort (including negligence or otherwise) arising in any way out of
-the use of this software, even if advised of the possibility of such damage.
-*/
-#include "opencv2/face/predict_collector.hpp"
-#include "opencv2/core/cvstd.hpp"
-namespace cv {
-namespace face {
-
-CV_WRAP bool StdPredictCollector::emit(const int label, const double dist, const int state) {
-    ((void)state);
-    ((void)label);
-    _s += pow(dist - _avg, 2);
-    _n++;
-    return true;
-}
-CV_WRAP double StdPredictCollector::getResult() {
-    return sqrt(_s / (_n - 1));
-}
-CV_WRAP Ptr<StdPredictCollector> StdPredictCollector::create(double threshold, double avg) {
-    return Ptr<StdPredictCollector>(new StdPredictCollector(threshold, avg));
-}
-
-
-}
-}
\ No newline at end of file

modules/face/src/topn_predict_collector.cpp

-/*
-By downloading, copying, installing or using the software you agree to this license.
-If you do not agree to this license, do not download, install,
-copy or use the software.
-
-
-License Agreement
-For Open Source Computer Vision Library
-(3-clause BSD License)
-
-Copyright (C) 2000-2015, Intel Corporation, all rights reserved.
-Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
-Copyright (C) 2009-2015, NVIDIA Corporation, all rights reserved.
-Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
-Copyright (C) 2015, OpenCV Foundation, all rights reserved.
-Copyright (C) 2015, Itseez Inc., all rights reserved.
-Third party copyrights are property of their respective owners.
-
-Redistribution and use in source and binary forms, with or without modification,
-are permitted provided that the following conditions are met:
-
-* Redistributions of source code must retain the above copyright notice,
-this list of conditions and the following disclaimer.
-
-* Redistributions in binary form must reproduce the above copyright notice,
-this list of conditions and the following disclaimer in the documentation
-and/or other materials provided with the distribution.
-
-* Neither the names of the copyright holders nor the names of the contributors
-may be used to endorse or promote products derived from this software
-without specific prior written permission.
-
-This software is provided by the copyright holders and contributors "as is" and
-any express or implied warranties, including, but not limited to, the implied
-warranties of merchantability and fitness for a particular purpose are disclaimed.
-In no event shall copyright holders or contributors be liable for any direct,
-indirect, incidental, special, exemplary, or consequential damages
-(including, but not limited to, procurement of substitute goods or services;
-loss of use, data, or profits; or business interruption) however caused
-and on any theory of liability, whether in contract, strict liability,
-or tort (including negligence or otherwise) arising in any way out of
-the use of this software, even if advised of the possibility of such damage.
-*/
-#include "opencv2/face/predict_collector.hpp"
-#include "opencv2/core/cvstd.hpp"
-#include <iterator>     // std::back_inserter
-namespace cv {
-namespace face {
-
-CV_WRAP bool TopNPredictCollector::emit(const int label, const double dist, const int state)
-{
-    ((void)state);
-    std::pair<int, double> p = std::make_pair(label, dist);
-    if (_idx->size() == 0 || p.second <= _idx->front().second) {
-        _idx->push_front(p);
-    } else if (p.second >= _idx->back().second) {
-        _idx->push_back(p);
-    }
-    else {
-        typedef std::list<std::pair<int,double> >::iterator it_type;
-        for (it_type i = _idx->begin(); i != _idx->end(); i++) {
-            if (p.second <= i->second) {
-                _idx->insert(i, p);
-                break;
-            }
-        }
-    }
-    return true;
-}
-
-CV_WRAP bool TopNPredictCollector::filter(int * label, double * dist, const int state)
-{
-    ((void)state);
-    if (_idx->size() < _size)return true; //not full - can insert;
-    if (*dist >= _idx->back().second)return false; //too far distance
-    for (std::list<std::pair<int, double> >::iterator it = _idx->begin(); it != _idx->end(); ++it) {
-        if (it->first == *label) {
-            if (it->second <= *dist) {
-                return false; //has more close
-            }
-            else {
-                _idx->erase(it);
-                return true; //no more require pop_back
-            }
-        }
-    }
-    _idx->pop_back();
-    return true;
-}
-
-CV_WRAP Ptr<std::list<std::pair<int, double> > > TopNPredictCollector::getResult()
-{
-    return _idx;
-}
-
-CV_WRAP std::vector<std::pair<int, double> > TopNPredictCollector::getResultVector()
-{
-    std::vector<std::pair<int, double> > result;
-    std::copy(_idx->begin(), _idx->end(), std::back_inserter(result));
-    return result;
-}
-
-CV_WRAP Ptr<TopNPredictCollector> TopNPredictCollector::create(size_t size, double threshold)
-{
-    return Ptr<TopNPredictCollector>(new TopNPredictCollector(size, threshold));
-}
-
-}
-}
\ No newline at end of file

modules/face/src/vector_predict_collector.cpp

-/*
-By downloading, copying, installing or using the software you agree to this license.
-If you do not agree to this license, do not download, install,
-copy or use the software.
-
-
-License Agreement
-For Open Source Computer Vision Library
-(3-clause BSD License)
-
-Copyright (C) 2000-2015, Intel Corporation, all rights reserved.
-Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
-Copyright (C) 2009-2015, NVIDIA Corporation, all rights reserved.
-Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
-Copyright (C) 2015, OpenCV Foundation, all rights reserved.
-Copyright (C) 2015, Itseez Inc., all rights reserved.
-Third party copyrights are property of their respective owners.
-
-Redistribution and use in source and binary forms, with or without modification,
-are permitted provided that the following conditions are met:
-
-* Redistributions of source code must retain the above copyright notice,
-this list of conditions and the following disclaimer.
-
-* Redistributions in binary form must reproduce the above copyright notice,
-this list of conditions and the following disclaimer in the documentation
-and/or other materials provided with the distribution.
-
-* Neither the names of the copyright holders nor the names of the contributors
-may be used to endorse or promote products derived from this software
-without specific prior written permission.
-
-This software is provided by the copyright holders and contributors "as is" and
-any express or implied warranties, including, but not limited to, the implied
-warranties of merchantability and fitness for a particular purpose are disclaimed.
-In no event shall copyright holders or contributors be liable for any direct,
-indirect, incidental, special, exemplary, or consequential damages
-(including, but not limited to, procurement of substitute goods or services;
-loss of use, data, or profits; or business interruption) however caused
-and on any theory of liability, whether in contract, strict liability,
-or tort (including negligence or otherwise) arising in any way out of
-the use of this software, even if advised of the possibility of such damage.
-*/
-#include "opencv2/face/predict_collector.hpp"
-#include "opencv2/core/cvstd.hpp"
-namespace cv {
-namespace face {
-CV_WRAP bool VectorPredictCollector::emit(const int label, const double dist, const int state)
-{
-    ((void)state);
-    _idx->push_back(std::pair<int, double>(label, dist));
-    return true;
-}
-Ptr<std::vector<std::pair<int, double> > > VectorPredictCollector::getResult()
-{
-    return _idx;
-}
-
-CV_WRAP std::vector<std::pair<int, double> > VectorPredictCollector::getResultVector()
-{
-    return (*_idx);
-}
-
-CV_WRAP Ptr<VectorPredictCollector> VectorPredictCollector::create(double threshold)
-{
-    return Ptr<VectorPredictCollector>(new VectorPredictCollector(threshold));
-}
-
-
-}
-}
\ No newline at end of file